CJS
We will use the dipper dataset, described as follows from Lebreton et. al 1992): There are four species of dippers (Cinclus spp.) recognized in the world. They inhabit mountain streams, feeding on underwater invertebrates. Their livelihood is closely dependent on streams; their nests of moss are always close to water, sometimes hidden behind waterfalls. Capture-recapture data on the European Dipper (Cinclus cinclus) were collected for 7 yr (k = 7) (1981-1987) by G. Marzolin in eastern France (Marzolin 1988). The data consist of marking and recaptures of breeding adults each year during the breeding period from early March to 1 June. Birds were at least 1 yr old when initially banded. A total of 294 birds were marked and the sex identified.
a) create models allowing combinations of time, group (sex), and no variation in apparent survival (Phi) and recapture
b) Suppose you think that instead of varying over time, survival varies as a function of which age (years after release) an individual belongs to. Hint: If you look at ‘dipper.ddl’ you will see that RMark can associate the cohorts with the name=’age’; via the formula=~age. Incorporate models in which survival is a function of age alone and of age and sex (additive) and combine these with the different possibilities for p (constant, sex specific, time specific, time and sex specific) . Is "age" as defined here the same as chronological age? Why or why not
c) Finally, examine the effects of flood on survival probabilities assuming additive affects with age; and also examine the additive effects of flood and sex. Assume combine these with the different possibilities for p (constant, sex specific, time specific, time and sex specific).
Hint: the above operations can be made easier (less typing, more automatic model creation) in RMark by use of the create.model.list() and mark.wrapper() functions. Check out the help feature for each of these to see some examples